12737results about "Volume/mass flow measurement" patented technology

The invention discloses a multi-point ditch flow monitoring method, and particularly relates to the field of branch ditch flow monitoring, which is used for solving the problem of complex branch ditch flow monitoring and optimization, and comprises the following steps of: constructing a branch ditch topological connection relation matrix, generating a flow characteristic curve in combination with flow and water level time sequence data, and marking interference points; generating an interference incidence matrix by utilizing two-channel interaction analysis, extracting upstream and downstream flow offset and disturbance propagation characteristics, judging an interference dominant mode according to a difference degree, and respectively calculating a flow offset compensation matrix and a disturbance propagation correction matrix; the recursive optimization model realizes segmented correction and reduces error residual errors, combines spatial-temporal feature clustering to identify abrupt change sections and generate a high-risk area key monitoring list, extracts refined data based on a high-frequency acquisition strategy to analyze abnormal causes, generates a dynamic correction result by using a prediction model, and updates a traffic balance data set. The multi-mode interference is accurately corrected, the flow distribution is optimized, and the monitoring precision and the system stability are improved.

Various automated techniques are disclosed herein for monitoring and assessing real-time and future operational and health statuses of real-world assets (e.g., physical devices, components, equipment, structures, buildings, machines, infrastructure, piping systems, etc.). A monitoring system incorporates the use of intelligent Monitoring Devices for monitoring pipe systems and / or other infrastructure for leaks / issues using IoT devices and machine learning. One or more Monitoring Device(s) are attached to specific physical equipment / structure(s) to be monitored. A Monitoring Device performs comprehensive field data gathering. The collected field data is used to train a customized ML model, which is stored locally in that Monitoring Device. The Monitoring Device monitors current conditions of the pipe using various sensors, and uses its locally stored customized, trained model to perform real-time, edge-based analysis of the monitored data to identify possible issues in real-time and / or to predict future maintenance / service needs without relying on continuous cloud connectivity.

The approach presented here relates to an analysis device (100) for analyzing a viscosity of a fluid (217). The analysis device (100) comprises a detection device (110) and a provisioning device (115). The detection device (110) is formed to determine the viscosity of the fluid (217) using at least one Doppler parameter of a Doppler spectrum of the fluid (217). The provisioning device (115) is formed to provide or transmit a viscosity signal that represents the viscosity determined by the detection device (110).

The invention relates to the technical field of graphics card power consumption adjustment, and discloses a method, a device and equipment for dynamically adjusting the power consumption of a graphics card component. The method comprises the following steps: carrying out multi-channel data acquisition and working load characteristic analysis on operation parameters of a graphics card GPU core, a video memory and a power management unit to obtain a component temperature state evaluation matrix; executing component-level power consumption distribution based on multi-objective optimization to obtain a power consumption distribution scheme of each component; inputting the power consumption distribution scheme of each component into a power consumption-frequency-voltage mapping model, and calculating an optimal frequency voltage configuration parameter through a binary search algorithm to obtain a frequency voltage control instruction; performing multi-step prediction to obtain a module power consumption demand prediction value; according to the method, the frequency voltage combination with the highest performance efficiency can be found under the condition that the power consumption constraint is met, and accurate power consumption control is achieved.

The invention relates to the technical field of hydrological monitoring, in particular to a multi-satellite collaborative hydrological monitoring system. The method comprises the following steps that a water level height measurement module obtains radar pulse recovery time delay data through a height measurement satellite and calculates the water level height, abnormal points are removed to generate river water level data, a water remote sensing module collects river water images through a remote sensing satellite to extract water boundary features, water area change data are deduced, and the water level height measurement module calculates the water level height. The meteorological wind shear analysis module obtains river channel meteorological data through a meteorological satellite, microwave scattering measurement and wind speed inversion are carried out, wind-induced shear stress parameters are generated, and the flow estimation module carries out section dynamic analysis and estimates the water flow in combination with river channel water level and water area data. And the flow correction module corrects the river water flow based on the wind-induced shear stress parameter and carries out real-time monitoring, and data are synchronously uploaded to the control terminal, so that comprehensive dynamic monitoring of the hydrological state of the river is realized. According to the invention, a more efficient multi-satellite collaborative hydrological monitoring system is realized.

The invention discloses a method for automatically adjusting a head wave detection voltage threshold value of an ultrasonic flowmeter, relates to the technical field of flow velocity measurement, and ensures that the ultrasonic flowmeter accurately identifies a head wave and measures the flow velocity under a complex working condition by dynamically detecting and adjusting the peak value of a received signal and a wave hopping phenomenon. The method comprises the following steps: S101, initializing a peak acquisition circuit, an adjustable potentiometer, a logic control circuit and a head wave trigger and zero-crossing control circuit of a system, and adjusting the gain of an amplifier; by dynamically monitoring the peak value of the ultrasonic receiving signal and adjusting the head wave triggering voltage threshold value, the accuracy of flow velocity measurement is remarkably improved, false triggering and missing triggering caused by a fixed threshold value are reduced, the measurement error is reduced, the measurement precision is improved, the head wave signal is reliably identified by an introduced front-back jump wave fine tuning mechanism, the measurement failure is prevented, and the accuracy of flow velocity measurement is improved. The ultrasonic flowmeter can stably work in a dynamically changing industrial environment, and the high-precision metering requirement is met.

A method for packaging digital evidence for long term validation comprises forming a package of a digital document (10), an electronic signature (12) for the document (10), together with evidence (16) of the authority of the signature in the document and a time stamp (20) indicating when the document was digitally signed. All of the pieces form parts of the packaged evidence.

A portable computer includes a display portion comprising a display and a base portion pivotally coupled to the display portion. The base portion may include a bottom case and a top case, formed from a dielectric material, coupled to the bottom case. The top case may include a top member defining a top surface of the base portion and a sidewall integrally formed with the top member and defining a side surface of the base portion. The portable computer may also include a sensing system including a first sensing system configured to determine a location of a touch input applied to the top surface of the base portion and a second sensing system configured to determine a force of the touch input.

A circuit board includes: a first plurality of integrated circuit (IC) chips, a second plurality of IC chips that is distinct from the first plurality of IC chips, a first power rail configured to provide power to the first plurality of IC chips, and a second power rail configured to provide power to the second plurality of IC chips. A controller is configured to receive sensor data from the first plurality of IC chips and the second plurality of IC chips and independently determine, based on the sensor data, a first power supply voltage for the first power rail and a second power supply voltage for the second power rail. The first power supply voltage and the second power supply voltage are different from one another. A power supply is configured to provide the first and second power supply voltages to the first and second power rails.

The invention relates to a power supply module which comprises an inductance circuit, a switch circuit, a check driving circuit and a controller, wherein the inductance circuit is provided with an inductor and a voltage feedback line, and the voltage feedback line feeds back the end voltage of the inductor. The switch circuit is electrically connected with the inductance circuit to drive the inductance circuit. The check driving circuit is electrically connected with the switch circuit and the voltage feedback line, and the check driving circuit controls the switch circuit and generates a current feedback signal according to the end voltage of the inductor. The controller is electrically connected with the check driving circuit, and controls the check driving circuit according to the current feedback signal.

The invention relates to the technical field of hydrological monitoring, and discloses a river flow monitoring method and system fusing multi-source data, and the method comprises the steps: collecting river flow data and river water level data through employing a high-precision sensor group, and collecting river image data through employing an unmanned plane; filtering the river flow data and the river water level data by adopting a Kalman filtering method to obtain filtered river flow data and filtered river water level data; performing edge detection on the riverway image data by adopting a Canny edge detection method to obtain riverway boundary information; on the basis of the riverway boundary information, a cubic spline interpolation method is adopted for interpolation, a smooth first boundary line and a smooth second boundary line are obtained, and the actual flow of the riverway is calculated on the basis of the filtered riverway water level data and the riverway flow velocity data; judging whether the actual flow of the riverway is greater than a riverway flow preset value, and if yes, sending alarm information; the actual flow of the river channel is calculated by fusing the multi-source data, and the accuracy of monitoring the flow of the river channel is improved.

Embodiments pertain to reducing power consumption in a computing system comprising one or more deterministic processors. A controller generates a plurality of control signals for a voltage regulator to regulate a supply voltage of a respective one of the one or more deterministic processors. A power management module determines an initial profile for power consumption and performance of an algorithm executed on the respective deterministic processor having an initial value for the supply voltage and an initial value for a clock frequency. The power management module further determines a target profile for power consumption and performance of the algorithm executed on the respective deterministic processor. The controller modifies the plurality of control signals based on the initial profile and the target profile. The respective deterministic processor executes the algorithm while the supply voltage is dynamically modified by the voltage regulator based on the modified plurality of control signals.

The invention discloses a power supply circuit, a server and a time sequence control method, relates to the field of server power supply, and solves the problem that the demand of loads such as a GPU (Graphics Processing Unit) and a CPU (Central Processing Unit) on short-time peak power is increasingly increased at present. According to the power supply circuit, the long-time power supply module and the peak value compensation module are introduced to work cooperatively, the long-time power supply module provides stable energy conversion, and the long-term stable power supply requirement of a load is met; and the peak compensation module dynamically adjusts power supply according to the load demand and the working state of the long-time power supply module, provides or recovers energy, and meets the instantaneous peak power demand, thereby avoiding the defect that the peak current cannot meet the requirement or needs a large-scale redundancy and high-cost capacitor row in the traditional scheme, and improving the reliability of the system. According to the design, power supply stability can be guaranteed, system cost and size are reduced, and overall power supply efficiency and response capability are improved.

The invention provides a measurement correction and optimization arrangement method for an external clamping type ultrasonic flowmeter in a disturbed flow field, which comprises the following steps of: firstly, simulating the disturbed flow field in an actual pipeline in an industrial field by using computational fluid mechanics simulation software to obtain accurate flow field distribution near disturbance; secondly, performing integration on each ultrasonic propagation path grid point in different measurement modes to obtain in-pipe flow velocity simulation values and section average velocity at positions with different lengths away from a disturbance point, multiplying the values by the section area to obtain uncorrected flow and standard reference flow, and comparing the uncorrected flow and the standard reference flow to obtain flow deviation distribution; and then establishing a function relationship between flow deviation distribution and sensor installation arrangement, and obtaining a measurement path combination enabling the flow deviation to be insensitive to a sensor installation angle through data analysis, thereby correcting measurement results at different positions of the downstream of the disturbance pipeline through quantitative correction factors. According to the method, the measurement result with the measurement error lower than 2% can be obtained in the straight pipe section range of ten times of the pipeline diameter at the downstream of the elbow pipe in an industrial field.

A system for controlling a charging of an electric vehicle, wherein a charging at one electric vehicle charging station affect a charging at another electric vehicle charging station is disclosed. The system includes: an electric power grid, a first electric vehicle charging station connected to the electric power grid, and a second electric vehicle charging station connected to the electric power grid, wherein the first electric vehicle charging station facilitates a charge transfer for an electric vehicle at the second electric vehicle charging station using a mobile device. The mobile device relays communication from the electric vehicle charging stations to the cloud server. The charge transfer request received at the cloud server is authorized using identification information and credit account information received from the mobile device. The charge transfer at the first electric vehicle charging station is adjusted based on a charging level at the second electric vehicle charging station.

A database system is operable to perform a power supply strategy selection function based on first energy utilization-based operation optimizer input data to generate first energy utilization-based power supply strategy data denoting, for each power supply type of a plurality of power supply types, a corresponding first proportion of power supply resources that be implemented as the each power supply type. A first set of power supply resources is selected to execute a first database operation based on the first energy utilization-based power supply strategy data. The first set of power supply resources are utilized to power a first set of computing devices to enable the first set of computing devices to participate in execution of the first database operation in accordance with the first energy utilization-based power supply strategy data.

The disclosed technology is directed to a computing device for detecting and preventing melting of a component of the computing device. In some examples, the computing device includes a cable that connects a power supply unit and an add-on card, and a thermal protection controller. Based on a sensor signal from a temperature sensor of the cable, the thermal protection controller determines that a temperature associated with the cable exceeds a threshold temperature. Responsive to determining that the temperature associated with the cable exceeds the threshold temperature, the thermal protection controller causes the power supply unit to cease supplying power to the add-on card by transmitting an overtemperature signal through the cable.

The invention relates to a method, device and product for monitoring river flow in real time, and the method comprises the steps: obtaining tower footing video data of a target river reach which comprises a target section and a pier buoy; inputting the tower footing video data into a water level and flow velocity identification model, and obtaining the water level elevation and the surface flow velocity of at least part of the cross section in the target section through the water level and flow velocity identification model; inputting the water surface elevation into a three-dimensional digital river channel model to obtain a section water passing area of a corresponding cross section; and obtaining the cross section flow of the target cross section according to the cross section water passing area and the surface flow velocity. According to the embodiment of the invention, automatic flow estimation based on the tower footing video can be realized, the manual measurement cost is reduced, the spatial-temporal resolution of flow monitoring is improved, and the method can be used for large-range river monitoring, especially in areas lacking hydrometric stations, and can provide data support for drainage basin water resource management and flood prevention early warning.

Disclosed herein is urinary output monitoring system including a urinary collection device having a flow meter in communication with a monitor. The urinary collection device catheter includes a urine collection bag, a drainage tube and a urinary catheter. A console of the flow meter wirelessly communicates with a console of the monitor. The monitor depicts urine flow rate information on a display and wirelessly transmits urine flow rate information to an EMR system. The flow meter includes a flow meter identifier and the system links the urine flow rate information to the flow meter identifier. The monitor further links the flow meter identifier with a patient identification from the EMR system and depicts the patient identification on the display.

The invention provides a gas ultrasonic transducer fast matching method, device and equipment and a storage medium, original measurement data such as flight time are obtained by deploying an ultrasonic transducer in a gas ultrasonic flowmeter in a gas conveying pipeline, and multi-dimensional data acquisition is carried out in combination with other sensor parameters. Wavelet noise reduction and dynamic time warping processing are carried out on collected signals, signal quality and time sequence consistency are improved, time domain, frequency domain, environment and statistical features are extracted, and multi-dimensional feature vectors are formed. Modeling is carried out through a time sequence feature branch and an environment feature branch, weighted fusion is carried out by adopting an attention mechanism, and the recognition capability of the model on key features is enhanced. A machine learning model is trained based on fusion features, a multi-objective loss function and a data enhancement strategy are adopted, the prediction precision and generalization ability of the model are improved, and a compensation value is output to calibrate the original traffic in real time. According to the method, the accuracy and stability of gas flow measurement in a complex environment are effectively improved, and the method has a good engineering application prospect.

A power management system is provided for powering a primary group of power consumers and a secondary group of power consumers. The primary group of power consumers include a data center including a plurality of first computing units. The secondary group of power consumers include a plurality of second computing units whose power consumption is adjustable to ensure the first computing units are continuously powered. The first computing units are in communication with a network for providing cloud services to remote client computers. The first computing units have an energy priority over the second computing units. The power management system includes power sources including a first power source and a second power source. The second power source is a power generation module configured to consume natural gas and continuously generate an electrical output sufficient to alternatively power the plurality of first computing units and the second computing units. The power management system also includes a monitoring and control system configured to receive status inputs including an operational status and / or an operational cost of each of the power sources, and power consumption metrics of the primary group of power consumers and / or the secondary group of power consumers. The monitoring and control system is also configured to output a control signal to decrease a power consumption by the secondary group of power consumers and to power the primary group of power consumers by the second power source as a function of the operational status and / or operational cost of each of the power sources.

A system for controlling a charging of an electric vehicle, wherein a charging at one electric vehicle charging station affect a charging at another electric vehicle charging station is disclosed. The system includes: an electric power grid, a first electric vehicle charging station connected to the electric power grid, and a second electric vehicle charging station connected to the electric power grid, wherein the first electric vehicle charging station facilitates a charge transfer for an electric vehicle at the second electric vehicle charging station using a mobile device. The mobile device relays communication from the electric vehicle charging stations to the cloud server. The charge transfer request received at the cloud server is authorized using identification information and credit account information received from the mobile device. The charge transfer at the first electric vehicle charging station is adjusted based on a charging level at the second electric vehicle charging station.

The invention relates to the technical field of flow measurement and control, and particularly discloses a cheese filling flow real-time calibration control method and system.The cheese filling flow real-time calibration control method comprises the following steps that working condition information of cheese in a filling pipeline is collected in real time, and the working condition information comprises the temperature, the pressure, an original flow signal, the pump rotating speed and the proportional valve opening degree; dynamically selecting a filtering order according to the signal-to-noise ratio of the original flow signal, and outputting the filtered flow; and based on the acquired working condition information, predicting the dynamic viscosity of the cheese in real time through a neural network, fitting a flow-working condition relation function and calculating a target flow value. The signal-to-noise ratio of an original flow signal is dynamically adapted to optimize filtering processing, signal distortion caused by interference such as temperature drift and mechanical vibration is effectively eliminated, and the flow detection precision is improved; by means of the neural network, the dynamic viscosity of cheese is predicted in real time, the model is dynamically adjusted, the problems that traditional viscosity estimation lags behind, and the batch adaptability is poor are solved, and an accurate basis is provided for flow target value calculation.

The invention relates to an ultrasonic flow metering device and a metering method thereof, and relates to the field of ultrasonic measuring devices. According to the metering device, through a cross-correlation operation circuit, a microcontroller, a double-threshold comparator, a peak detector, a gain adjustment circuit and a head wave threshold adjustment circuit, self-adaptive processing and adjustment of echo signals and head wave thresholds are achieved, and the accuracy and reliability of flow metering are improved. The metering method adopts an adaptive adjustment strategy of echo signal amplifier gain based on an output signal of an echo signal peak detection circuit, and a head wave threshold adaptive adjustment strategy based on a correlation operation value of echo signal sampling data and pre-stored reference wave data. According to the scheme, the stability of the echo signal and the rationality of the head wave threshold value are guaranteed, the method has adaptability to echo contour feature changes caused by transducer aging or contamination, and then the reliability of the flow metering process is guaranteed.

The invention provides an intelligent water and soil conservation monitoring and management system, and belongs to the technical field of hydraulic engineering and environment monitoring. The data acquisition layer acquires data in real time by using an acoustic sensor network, machine vision monitoring equipment, Internet of Things monitoring equipment, satellite remote sensing monitoring, unmanned aerial vehicle inspection and other technologies. And the data transmission layer transmits the acquired data to the data processing and analyzing layer by adopting a wireless communication network. The data processing and analysis layer analyzes multi-source data through data fusion and preprocessing, GIS technology application and big data analysis and machine learning. And the decision support and application layer comprises a prevention and control measure generation and optimization unit, a real-time early warning and emergency response unit and a user interaction and decision support unit, provides a water and soil conservation and dike reinforcement strategy for a user, and has a feedback optimization mechanism. By comprehensively applying various monitoring technologies and data analysis methods, the accuracy and timeliness of water and soil loss monitoring are improved, and powerful guarantee is provided for dike safety.

An optimization method based on measurement data of an ultrasonic gas meter, includes: if a relative strength index obtained by analysis does not meet expectation, calculating the degree of influence of a measurement condition on the relative strength index and determining whether to compensate the measurement data of the gas meter according to magnitude of the degree of influence; constructing an initial compensation model for the measurement data of the gas meter; performing sensitivity analysis on the optimized compensation model after multi-variable optimization; completing the correction of display data of the gas meter by a compensation factor combined with real-time temperature and pressure data and obtaining fluid features in a pipeline; matching the gas meter with the corresponding optimization plan from the pre-constructed gas meter optimization knowledge graph based on the correspondence between the fluid features and an optimization plan; and executing the optimization plan to optimize the gas meter.

The embodiment of the invention provides a data center energy consumption prediction method and system based on DCIM. Real-time operation parameters of an electric quantity monitoring module, a refrigeration equipment control module and an environment sensing module are synchronously obtained through a heterogeneous data bus, a dynamic topology calibration mechanism is adopted to carry out space-time alignment processing so as to generate a dynamic topology matrix, and a propagation path weight matrix is constructed; according to a timestamp sequence of a historical equipment start-stop event and an energy consumption fluctuation curve phase offset, an event trigger signal is injected into a propagation path weight matrix to form a multi-dimensional prediction map, a key propagation path identifier is positioned by using a path traceability mechanism based on transient peak distribution and real-time environmental parameter phase deviation in the prediction map, and a target propagation path is obtained. And adjusting an impedance coefficient and a pressure loss threshold value in the propagation path weight matrix so as to generate a refrigeration equipment power gradient adjustment instruction and a power supply link impedance matching instruction. According to the technical scheme provided by the embodiment of the invention, the energy efficiency management and operation stability are effectively improved.

The invention relates to the technical field of automatic control, in particular to an intelligent Internet of Things water meter control method and system.The intelligent Internet of Things water meter control method comprises the steps that the water consumption of a water meter at the current time node is obtained, the water consumption of the current time node is input into an improved machine learning model, the water consumption state of the current time node is output, and if the water consumption state is abnormal, the water meter is started; if yes, controlling the water meter to send out an early warning signal and stopping water supply; wherein the improved machine learning model comprises the steps of carrying out iterative training on the machine learning model by utilizing a loss function and calculating a loss function value of a current time node, and the historical loss function value is positively correlated with the abnormal degree of the water consumption of the historical time node and is inversely correlated with the surge coefficient of the water consumption of the historical time node. According to the method, the problem that the overall performance and reliability of the intelligent water meter are not high possibly due to potential insufficiency of an existing algorithm in the aspects of detection efficiency and accuracy is solved.

The present disclosure provides a method for measuring flow velocity of multilayer groundwater using distributed optical fiber with point-source active heating, comprising: setting and optimizing field test parameters; conducting a background temperature monitoring test; performing a point-source active heating distributed temperature measurement test, including conducting multiple rounds of heating tests; denoising the obtained multi-point source thermal plume attenuation signal data of the groundwater; searching for the peak value of temperature-permeability curve based on an automatic multi-scale peak search algorithm; performing secondary processing on the peak data; estimating the groundwater flow velocity. The method of the present disclosure solves the problem that the existing groundwater flow velocity measurement technology cannot simultaneously measure multiple points and multiple layers, and it can avoid groundwater contamination during the measurement process.

The approach presented here relates to an analysis device for analyzing a viscosity of a fluid. The analysis device comprises a detection device and a provisioning device. The detection device is formed to determine the viscosity of the fluid using at least one Doppler parameter of a Doppler spectrum of the fluid. The provisioning device is formed to provide or transmit a viscosity signal that represents the viscosity determined by the detection device.